Продукты и решения Informatica

Editor's Notes

1. Key Points: Nearly 3,000 customers in every vertical market and across the globe. Leading brands who have all chosen Informatica as their platform of choice. NOTE: IT IS IMPORTANT THAT YOU UNDERSTAND WHAT CUSTOMERS ARE DOING WITH OUR SOLUTIONS. PLEASE HIGHLIGHT SPECIFIC CUSTOMERS THAT ARE RELEVANT TO YOUR INDUSTRY AND PROSPECT. DO YOUR HOMEWORK – BE PREPARED. Example Text: Every quarter we are delighted that new logo’s join our community. Here are a selection of companies that are references across different verticals and across the globe. Nearly 3,000 different companies have chosen Informatica as their platform of choice to empower them to access, integrate and trust all their information assets. Transition: With that, I’d like to thank you for your time today. Is thee anything else that I can share with you and how do we proceed?
2. Many types of interface, but PowerExchange handles all the complexity Optimized, high-performance native interfaces Metadata automatically imported (from database, copybooks, other artifacts) ODBC is fallback Some inherently batch, others inherently real-time Change data capture (CDC) for most databases can be accessed either batch or real-time Historical Formerly, PowerExchange just meant only mainframe, midrange, and CDC PowerCenter Connect Options or PowerConnect are older terms for the non-PowerExchange access technology
3. A PowerCenter task spawns a multi-threaded process to facilitates the extraction, transformation, and load necessary for a data integration task. Memory Buffer Pool -- forward animation PowerCenter uses an in memory buffer pool which is loaded as the data is extracted from its original location. This buffer pool is divided into smaller blocks of memory that will act as the vehicle for moving the data along its journey. This buffer pool is used as a pipeline to make the data available to each component of the defined data integration process by keeping each thread in the process busy. Partition Point -- forward animation PowerCenter facilitates this each of these unique tasks by interrogating the defined transformation rules. When PowerCenter finds either logical or user defined similarly grouped tasks it creates a boundary called a partition point. Once the partition points are defined, threads are spawned to execute each of the respective tasks that have been assigned to it. These thread working with the buffer pool work in parallel to efficiently integrate the data. There is a provider thread (note there could be more than one) that load the buffer pool with data from the original data structures. There are one or more transformation threads responsible for applying integration logic defined within the client tools There is a consumer thread (note there could be more than one) that unloads the buffer pool for the data consumer. Parallel Processing -- forward animation As data is loaded into the pipeline, it is marked as being ready for transformation. The first transformation thread then executes integration tasks it has been assigned upon the data without ever moving it and the marks it as being ready for the next thread. If other transformation thread exist, it then applies its executes its tasks as the first and marks the data as being ready for the next thread until all transformation threads have been completed. Then the consumer thread unloads the data for the consumer once completed the block is marked as being ready to start the journey again. Keeping in mind that each thread is executing upon blocks as they are made available, thus processing the data in parallel.
4. Mapping Architect for Visio is one of Informatica’s best kept secrets and many of you already have it with PowerCenter. Mapping Architect for Visio enables architects to create Visio templates for common data integration patterns (e.g. slow-moving dimensions, data migrations, etc.) that can be used to automatically generate PowerCenter mappings. These templates can provide tremendous benefits in terms of development productivity and efficiency. For example, one customer built 7 templates that were used across 2 projects to generate 600 mappings. 97% of these mappings were automatically generated and required no additional changes. Another customer created a template which was used to create 150 mappings for a data migration project in less than a day. This normally would have taken about 2 weeks to create the 150 mappings. [CLICK] In PowerCenter 9.0, Mapping Architect for Visio now supports PowerExchange data sources, [CLICK] additional transformations such as midstream normalizer transformations, [CLICK] and transformation shortcuts. [CLICK] You can also configure and edit custom transformations after mapping generation which enables you to use these templates in more and more situations.
5. Informatica Metadata Manager helps you browse and analyze metadata from disparate metadata repositories so that you can understand and manage how information and processes are derived. [CLICK] Metadata is imported into a metadata management warehouse repository that provides [CLICK] a consolidated metadata catalog, enables personalized data lineage, and supports multiple business glossaries of business terms organized into categories and sub-categories. [CLICK] Metadata reports enable users to view dependencies between objects, view activities and identify problems. Through a URL API you can access business glossary terms and metadata manager lineage diagrams from 3 rd party BI applications.
6. In Metadata Manager 9.0 we improved the usability and clarity of the lineage diagram to further enhance the understanding of where the data is coming from and where it is being used.
7. The figure shows the service oriented view of the Enterprise Integration architecture. All backend IT assets are accessed through Data and Application Services over standard web services protocols.
8. Second, Informatica’s Data Transformation is flexible. With this product our customers can build embeddable, reusable data transformation services that can be dropped-in to any infrastructure – in both real-time and batch scenarios. Our transformation engine is SOA-Ready. The same transformations and the same engine can be leveraged in an ESB, with EAI, and obviously from within PowerCenter – but also as a common service, to access information from legacy systems, and within B2B Data Exchanges – even if it’s not Informatica’s. <optional> Wells Fargo, for example, uses B2B Data Transformation for NACHA, SWIFT, EDI, and custom formats across their EAI, ESB and MFT infrastructures.
9. Introduction: Now lets look at the activities of a data steward or business analyst. Traditionally he/she runs some macros or code in a spreadsheet or database to test the data for data quality errors. If the steward finds issues, he make notes and emails the notes to IT development to specify what needs to change. Nobody is completely happy with the process. Its too long, too inefficient, not scalable, no confidence in the process. Main points: With Informatica 9, <click> all the major tasks of a business analysts and data stewards are supported within the browser <click> profile data, analyse the data, and then drill down to identify anomalies <click>h
10. Introduction: Today line of business managers, responsible for applications (CRM, ERP or BI applications ) or processes (e.g. order to cash process, marketing campaigns, compliance processes) have no direct visibility or understanding of how their areas of responsibility are impacted by poor data quality. With V9 and pervasive data quality – that is all about to change. Main points: With V9 and using a browser, a line of business manager can: view a scorecard and drill down on the data, interprets the business impact – e.g. delays in invoicing Take action, working with a data analyst or data steward In this way, V9 makes data quality relevant to the business - the “easy to share” browser based scorecards for the line of business managers increases awareness of the business impact of poor data quality on their processes and applications and accelerates resolution – it makes data quality very personal!
11. AIB: AIB is the largest bank in Ireland and the 5th largest in Poland. In Ireland, the bank has a customer data warehouse with 7 million records. CUSTOMER SINCE: 2003 MAIN PROJECTS: Major projects include CRM initiatives and Compliance initiatives CRM initiatives AIB have a range of database and datawarehouse applications. Data Quality processes were needed to implement standardization rules across all master data to support a range of mailings to customers. A team of 10 data analysts were empowered to use ATHANOR to cleanse all customers data. 2. Compliance initiative The bank is implementing a major risk infrastructure to support several compliance initiatives. There is a clear requirement for data quality reporting in the form of Data Accuracy Scorecards – which Informatica Data Quality is providing. Implementation partners: Accenture KEY BENEFITS: Compliance processes fulfilled CRM processes supported Data Analysts enabled
12. OLTP – Транзакционные системы Банка STANDBY – Реплики транзакционных систем, позволяющие снять нагрузку с продукционных систем при захвате данных ETL -1 - Извлечение данных из систем-источников в staging -область ( STTI ). Структура данных не меняется для минимизации нагрузки на источники. STTI – Область данных DWH содержащая измененные неочищенные  данные (инкремент) из транзакционных систем ETL -2 - Процесс перегрузки данных из staging -области в оперативное хранилище данных ( ODS ). Данные при этом проходят контроль технического качества и отфильтровываются. Структура данных не меняется. ODS -  Область данных DWH содержащая измененные и очищенные в соответствии с критериями качества данные (инкремент) из транзакционных систем ETL -3 - Загрузка качественных данных из ODS в историческое хранилище ( DWH ). Данные претерпевают существенные изменения в соответствии с моделью DWH : происходит генерация суррогатных ключей, перегруппировка полей, согласование данных. DWH -  Область данных DWH содержащая очищенные, согласованные и исторические данные из транзакционных систем ETL -4 - Загрузка данных из DWH в витрины данных ( FADM , CAPSTONE _ FIN и т. д.). Используется подмножество данных хранилища. Помимо загрузки "один к одному", выполняется  агрегация данных и формирование вычисляемых полей. Analytical Data – пользовательские витрины данных Analytical middleware , Analytical front - end – аналитические системы, системы отчетности и пр.   Потоки данных: Синие – ETL -процессы ПО Informatica Зеленые– ETL -процессы ПО Oracle (материализованные представления) Белые – ETL -процессы ПО SAS
13. AIB: AIB is the largest bank in Ireland and the 5th largest in Poland. In Ireland, the bank has a customer data warehouse with 7 million records. CUSTOMER SINCE: 2003 MAIN PROJECTS: Major projects include CRM initiatives and Compliance initiatives CRM initiatives AIB have a range of database and datawarehouse applications. Data Quality processes were needed to implement standardization rules across all master data to support a range of mailings to customers. A team of 10 data analysts were empowered to use ATHANOR to cleanse all customers data. 2. Compliance initiative The bank is implementing a major risk infrastructure to support several compliance initiatives. There is a clear requirement for data quality reporting in the form of Data Accuracy Scorecards – which Informatica Data Quality is providing. Implementation partners: Accenture KEY BENEFITS: Compliance processes fulfilled CRM processes supported Data Analysts enabled
14. AIB: AIB is the largest bank in Ireland and the 5th largest in Poland. In Ireland, the bank has a customer data warehouse with 7 million records. CUSTOMER SINCE: 2003 MAIN PROJECTS: Major projects include CRM initiatives and Compliance initiatives CRM initiatives AIB have a range of database and datawarehouse applications. Data Quality processes were needed to implement standardization rules across all master data to support a range of mailings to customers. A team of 10 data analysts were empowered to use ATHANOR to cleanse all customers data. 2. Compliance initiative The bank is implementing a major risk infrastructure to support several compliance initiatives. There is a clear requirement for data quality reporting in the form of Data Accuracy Scorecards – which Informatica Data Quality is providing. Implementation partners: Accenture KEY BENEFITS: Compliance processes fulfilled CRM processes supported Data Analysts enabled
15. AIB: AIB is the largest bank in Ireland and the 5th largest in Poland. In Ireland, the bank has a customer data warehouse with 7 million records. CUSTOMER SINCE: 2003 MAIN PROJECTS: Major projects include CRM initiatives and Compliance initiatives CRM initiatives AIB have a range of database and datawarehouse applications. Data Quality processes were needed to implement standardization rules across all master data to support a range of mailings to customers. A team of 10 data analysts were empowered to use ATHANOR to cleanse all customers data. 2. Compliance initiative The bank is implementing a major risk infrastructure to support several compliance initiatives. There is a clear requirement for data quality reporting in the form of Data Accuracy Scorecards – which Informatica Data Quality is providing. Implementation partners: Accenture KEY BENEFITS: Compliance processes fulfilled CRM processes supported Data Analysts enabled
16. AIB: AIB is the largest bank in Ireland and the 5th largest in Poland. In Ireland, the bank has a customer data warehouse with 7 million records. CUSTOMER SINCE: 2003 MAIN PROJECTS: Major projects include CRM initiatives and Compliance initiatives CRM initiatives AIB have a range of database and datawarehouse applications. Data Quality processes were needed to implement standardization rules across all master data to support a range of mailings to customers. A team of 10 data analysts were empowered to use ATHANOR to cleanse all customers data. 2. Compliance initiative The bank is implementing a major risk infrastructure to support several compliance initiatives. There is a clear requirement for data quality reporting in the form of Data Accuracy Scorecards – which Informatica Data Quality is providing. Implementation partners: Accenture KEY BENEFITS: Compliance processes fulfilled CRM processes supported Data Analysts enabled
17. Текущий объем ЕХД: Детальный слой ~ 1,64Т Слой DataMart ( витрины ) ~ 2,8 T Ежедневный прирост (на текущий момент): 5-10G Количество витрин (на текущий момент): 87 Время загрузки за 1 операционный день: STG (~2 часа ) DWH (~2 часа ) DM (1-3 часа )
18. AIB: AIB is the largest bank in Ireland and the 5th largest in Poland. In Ireland, the bank has a customer data warehouse with 7 million records. CUSTOMER SINCE: 2003 MAIN PROJECTS: Major projects include CRM initiatives and Compliance initiatives CRM initiatives AIB have a range of database and datawarehouse applications. Data Quality processes were needed to implement standardization rules across all master data to support a range of mailings to customers. A team of 10 data analysts were empowered to use ATHANOR to cleanse all customers data. 2. Compliance initiative The bank is implementing a major risk infrastructure to support several compliance initiatives. There is a clear requirement for data quality reporting in the form of Data Accuracy Scorecards – which Informatica Data Quality is providing. Implementation partners: Accenture KEY BENEFITS: Compliance processes fulfilled CRM processes supported Data Analysts enabled
19. AIB: AIB is the largest bank in Ireland and the 5th largest in Poland. In Ireland, the bank has a customer data warehouse with 7 million records. CUSTOMER SINCE: 2003 MAIN PROJECTS: Major projects include CRM initiatives and Compliance initiatives CRM initiatives AIB have a range of database and datawarehouse applications. Data Quality processes were needed to implement standardization rules across all master data to support a range of mailings to customers. A team of 10 data analysts were empowered to use ATHANOR to cleanse all customers data. 2. Compliance initiative The bank is implementing a major risk infrastructure to support several compliance initiatives. There is a clear requirement for data quality reporting in the form of Data Accuracy Scorecards – which Informatica Data Quality is providing. Implementation partners: Accenture KEY BENEFITS: Compliance processes fulfilled CRM processes supported Data Analysts enabled